Overview

Dataset statistics

Number of variables16
Number of observations2988181
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory364.8 MiB
Average record size in memory128.0 B

Variable types

Numeric13
Categorical3

Alerts

publisher_id has constant value "0"Constant
article_id is highly overall correlated with category_idHigh correlation
category_id is highly overall correlated with article_idHigh correlation
click_timestamp is highly overall correlated with created_at_ts and 2 other fieldsHigh correlation
created_at_ts is highly overall correlated with click_timestamp and 2 other fieldsHigh correlation
session_id is highly overall correlated with click_timestamp and 2 other fieldsHigh correlation
session_start is highly overall correlated with click_timestamp and 2 other fieldsHigh correlation
click_environment is highly imbalanced (87.9%)Imbalance
click_deviceGroup is highly imbalanced (50.5%)Imbalance

Reproduction

Analysis started2024-05-20 19:07:56.854041
Analysis finished2024-05-20 19:17:00.296129
Duration9 minutes and 3.44 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

user_id
Real number (ℝ)

Distinct322897
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107947.83
Minimum0
Maximum322896
Zeros8
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:01.033983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6370
Q140341
median86229
Q3163261
95-th percentile274162
Maximum322896
Range322896
Interquartile range (IQR)122920

Descriptive statistics

Standard deviation83648.361
Coefficient of variation (CV)0.77489621
Kurtosis-0.46866505
Mean107947.83
Median Absolute Deviation (MAD)57248
Skewness0.72311891
Sum3.2256764 × 1011
Variance6.9970484 × 109
MonotonicityNot monotonic
2024-05-20T21:17:02.118178image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5890 1232
 
< 0.1%
73574 939
 
< 0.1%
15867 900
 
< 0.1%
80350 783
 
< 0.1%
15275 746
 
< 0.1%
2151 722
 
< 0.1%
4568 529
 
< 0.1%
12897 513
 
< 0.1%
11521 502
 
< 0.1%
34541 501
 
< 0.1%
Other values (322887) 2980814
99.8%
ValueCountFrequency (%)
0 8
 
< 0.1%
1 12
 
< 0.1%
2 4
 
< 0.1%
3 17
 
< 0.1%
4 7
 
< 0.1%
5 87
< 0.1%
6 35
< 0.1%
7 22
 
< 0.1%
8 56
< 0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
322896 2
< 0.1%
322895 2
< 0.1%
322894 2
< 0.1%
322893 2
< 0.1%
322892 2
< 0.1%
322891 2
< 0.1%
322890 2
< 0.1%
322889 2
< 0.1%
322888 2
< 0.1%
322887 3
< 0.1%

session_id
Real number (ℝ)

HIGH CORRELATION 

Distinct1048594
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5074722 × 1015
Minimum1.5068254 × 1015
Maximum1.5082114 × 1015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:03.006127image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.5068254 × 1015
5-th percentile1.5069418 × 1015
Q11.5071242 × 1015
median1.5074933 × 1015
Q31.5077494 × 1015
95-th percentile1.5081532 × 1015
Maximum1.5082114 × 1015
Range1.3859559 × 1012
Interquartile range (IQR)6.2526185 × 1011

Descriptive statistics

Standard deviation3.8552446 × 1011
Coefficient of variation (CV)0.00025574233
Kurtosis-1.1113892
Mean1.5074722 × 1015
Median Absolute Deviation (MAD)3.3299497 × 1011
Skewness0.18075988
Sum3.5943168 × 1018
Variance1.4862911 × 1023
MonotonicityNot monotonic
2024-05-20T21:17:04.263054image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.507563658 × 1015124
 
< 0.1%
1.507896573 × 1015107
 
< 0.1%
1.507133568 × 1015106
 
< 0.1%
1.507309773 × 101598
 
< 0.1%
1.508112331 × 101594
 
< 0.1%
1.507647366 × 101592
 
< 0.1%
1.507475404 × 101586
 
< 0.1%
1.506959499 × 101582
 
< 0.1%
1.508154737 × 101579
 
< 0.1%
1.506999909 × 101575
 
< 0.1%
Other values (1048584) 2987238
> 99.9%
ValueCountFrequency (%)
1.506825423 × 10152
< 0.1%
1.506825426 × 10152
< 0.1%
1.506825435 × 10152
< 0.1%
1.506825443 × 10152
< 0.1%
1.506825528 × 10152
< 0.1%
1.506825541 × 10153
< 0.1%
1.506825553 × 10152
< 0.1%
1.506825568 × 10152
< 0.1%
1.506825573 × 10153
< 0.1%
1.506825599 × 10152
< 0.1%
ValueCountFrequency (%)
1.508211379 × 10152
 
< 0.1%
1.508211376 × 10152
 
< 0.1%
1.508211372 × 10152
 
< 0.1%
1.508211369 × 10157
< 0.1%
1.508211367 × 10152
 
< 0.1%
1.508211353 × 10154
< 0.1%
1.508211348 × 10152
 
< 0.1%
1.508211326 × 10152
 
< 0.1%
1.508211326 × 10154
< 0.1%
1.508211324 × 10152
 
< 0.1%

session_start
Real number (ℝ)

HIGH CORRELATION 

Distinct646874
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5074722 × 1012
Minimum1.5068254 × 1012
Maximum1.5082114 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:05.151789image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.5068254 × 1012
5-th percentile1.5069418 × 1012
Q11.5071242 × 1012
median1.5074933 × 1012
Q31.5077494 × 1012
95-th percentile1.5081532 × 1012
Maximum1.5082114 × 1012
Range1.385956 × 109
Interquartile range (IQR)6.25262 × 108

Descriptive statistics

Standard deviation3.8552446 × 108
Coefficient of variation (CV)0.00025574233
Kurtosis-1.1113892
Mean1.5074722 × 1012
Median Absolute Deviation (MAD)3.32995 × 108
Skewness0.18075988
Sum4.5045999 × 1018
Variance1.4862911 × 1017
MonotonicityNot monotonic
2024-05-20T21:17:06.037713image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.507563657 × 1012127
 
< 0.1%
1.507896573 × 1012112
 
< 0.1%
1.507133567 × 1012108
 
< 0.1%
1.507309773 × 101298
 
< 0.1%
1.507647366 × 101297
 
< 0.1%
1.508112331 × 101296
 
< 0.1%
1.506959499 × 101287
 
< 0.1%
1.507651543 × 101287
 
< 0.1%
1.507475403 × 101286
 
< 0.1%
1.508154737 × 101285
 
< 0.1%
Other values (646864) 2987198
> 99.9%
ValueCountFrequency (%)
1.506825423 × 10122
< 0.1%
1.506825426 × 10122
< 0.1%
1.506825435 × 10122
< 0.1%
1.506825442 × 10122
< 0.1%
1.506825528 × 10122
< 0.1%
1.506825541 × 10123
< 0.1%
1.506825553 × 10122
< 0.1%
1.506825568 × 10122
< 0.1%
1.506825573 × 10123
< 0.1%
1.506825599 × 10122
< 0.1%
ValueCountFrequency (%)
1.508211379 × 10122
 
< 0.1%
1.508211376 × 10122
 
< 0.1%
1.508211372 × 10122
 
< 0.1%
1.508211369 × 10127
< 0.1%
1.508211367 × 10122
 
< 0.1%
1.508211353 × 10124
< 0.1%
1.508211348 × 10122
 
< 0.1%
1.508211326 × 10122
 
< 0.1%
1.508211325 × 10124
< 0.1%
1.508211324 × 10122
 
< 0.1%

session_size
Real number (ℝ)

Distinct72
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9018851
Minimum2
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:06.915426image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median3
Q34
95-th percentile9
Maximum124
Range122
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.9299415
Coefficient of variation (CV)1.0071905
Kurtosis158.46089
Mean3.9018851
Median Absolute Deviation (MAD)1
Skewness9.0900749
Sum11659539
Variance15.44444
MonotonicityNot monotonic
2024-05-20T21:17:07.883951image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1260372
42.2%
3 670185
22.4%
4 374240
 
12.5%
5 220105
 
7.4%
6 135762
 
4.5%
7 88354
 
3.0%
8 58544
 
2.0%
9 40878
 
1.4%
10 29530
 
1.0%
11 21714
 
0.7%
Other values (62) 88497
 
3.0%
ValueCountFrequency (%)
2 1260372
42.2%
3 670185
22.4%
4 374240
 
12.5%
5 220105
 
7.4%
6 135762
 
4.5%
7 88354
 
3.0%
8 58544
 
2.0%
9 40878
 
1.4%
10 29530
 
1.0%
11 21714
 
0.7%
ValueCountFrequency (%)
124 124
< 0.1%
107 107
< 0.1%
106 106
< 0.1%
98 98
< 0.1%
94 94
< 0.1%
92 92
< 0.1%
86 86
< 0.1%
82 82
< 0.1%
79 79
< 0.1%
75 75
< 0.1%

click_timestamp
Real number (ℝ)

HIGH CORRELATION 

Distinct2983198
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5074743 × 1012
Minimum1.5068268 × 1012
Maximum1.5106035 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:08.829795image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.5068268 × 1012
5-th percentile1.5069432 × 1012
Q11.5071269 × 1012
median1.5074949 × 1012
Q31.507751 × 1012
95-th percentile1.5081552 × 1012
Maximum1.5106035 × 1012
Range3.7766549 × 109
Interquartile range (IQR)6.2415175 × 108

Descriptive statistics

Standard deviation3.8585096 × 108
Coefficient of variation (CV)0.00025595857
Kurtosis-1.0926869
Mean1.5074743 × 1012
Median Absolute Deviation (MAD)3.3326927 × 108
Skewness0.18427149
Sum4.504606 × 1018
Variance1.4888096 × 1017
MonotonicityNot monotonic
2024-05-20T21:17:09.745810image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.507554094 × 10123
 
< 0.1%
1.507984106 × 10123
 
< 0.1%
1.507905589 × 10123
 
< 0.1%
1.506975362 × 10123
 
< 0.1%
1.507052449 × 10123
 
< 0.1%
1.508164975 × 10123
 
< 0.1%
1.50696101 × 10123
 
< 0.1%
1.507320444 × 10123
 
< 0.1%
1.506956077 × 10123
 
< 0.1%
1.507550142 × 10122
 
< 0.1%
Other values (2983188) 2988152
> 99.9%
ValueCountFrequency (%)
1.5068268 × 10121
< 0.1%
1.506826802 × 10121
< 0.1%
1.506826804 × 10121
< 0.1%
1.506826814 × 10121
< 0.1%
1.506826819 × 10121
< 0.1%
1.506826823 × 10121
< 0.1%
1.506826828 × 10121
< 0.1%
1.50682683 × 10121
< 0.1%
1.506826831 × 10121
< 0.1%
1.506826832 × 10121
< 0.1%
ValueCountFrequency (%)
1.510603455 × 10121
< 0.1%
1.510603425 × 10121
< 0.1%
1.510093913 × 10121
< 0.1%
1.510093883 × 10121
< 0.1%
1.509798423 × 10121
< 0.1%
1.509798393 × 10121
< 0.1%
1.509736674 × 10121
< 0.1%
1.509709959 × 10121
< 0.1%
1.50956166 × 10121
< 0.1%
1.509561584 × 10121
< 0.1%

click_environment
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 MiB
4
2904478 
2
 
79743
1
 
3960

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2988181
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

Length

2024-05-20T21:17:10.615808image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-20T21:17:11.227380image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

Most occurring characters

ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 2904478
97.2%
2 79743
 
2.7%
1 3960
 
0.1%

click_deviceGroup
Categorical

IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 MiB
1
1823162 
3
1047086 
4
 
117640
5
 
283
2
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2988181
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

Length

2024-05-20T21:17:11.845164image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-20T21:17:12.441176image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1823162
61.0%
3 1047086
35.0%
4 117640
 
3.9%
5 283
 
< 0.1%
2 10
 
< 0.1%

click_os
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.277603
Minimum2
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:12.993675image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median17
Q317
95-th percentile20
Maximum20
Range18
Interquartile range (IQR)15

Descriptive statistics

Standard deviation6.8817184
Coefficient of variation (CV)0.51829523
Kurtosis-0.93175147
Mean13.277603
Median Absolute Deviation (MAD)0
Skewness-0.95411713
Sum39675882
Variance47.358048
MonotonicityNot monotonic
2024-05-20T21:17:13.784746image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
17 1738138
58.2%
2 788699
26.4%
20 369586
 
12.4%
12 60096
 
2.0%
13 23711
 
0.8%
19 6384
 
0.2%
5 1513
 
0.1%
3 54
 
< 0.1%
ValueCountFrequency (%)
2 788699
26.4%
3 54
 
< 0.1%
5 1513
 
0.1%
12 60096
 
2.0%
13 23711
 
0.8%
17 1738138
58.2%
19 6384
 
0.2%
20 369586
 
12.4%
ValueCountFrequency (%)
20 369586
 
12.4%
19 6384
 
0.2%
17 1738138
58.2%
13 23711
 
0.8%
12 60096
 
2.0%
5 1513
 
0.1%
3 54
 
< 0.1%
2 788699
26.4%

click_country
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.357656
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:14.642677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum11
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.725861
Coefficient of variation (CV)1.2712063
Kurtosis21.55276
Mean1.357656
Median Absolute Deviation (MAD)0
Skewness4.8022523
Sum4056922
Variance2.9785961
MonotonicityNot monotonic
2024-05-20T21:17:15.253193image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 2852406
95.5%
10 61377
 
2.1%
11 29999
 
1.0%
8 9556
 
0.3%
6 7256
 
0.2%
9 6746
 
0.2%
2 6101
 
0.2%
3 4540
 
0.2%
5 3498
 
0.1%
4 3389
 
0.1%
ValueCountFrequency (%)
1 2852406
95.5%
2 6101
 
0.2%
3 4540
 
0.2%
4 3389
 
0.1%
5 3498
 
0.1%
6 7256
 
0.2%
7 3313
 
0.1%
8 9556
 
0.3%
9 6746
 
0.2%
10 61377
 
2.1%
ValueCountFrequency (%)
11 29999
1.0%
10 61377
2.1%
9 6746
 
0.2%
8 9556
 
0.3%
7 3313
 
0.1%
6 7256
 
0.2%
5 3498
 
0.1%
4 3389
 
0.1%
3 4540
 
0.2%
2 6101
 
0.2%

click_region
Real number (ℝ)

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.313314
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:15.976045image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q113
median21
Q325
95-th percentile27
Maximum28
Range27
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.0640064
Coefficient of variation (CV)0.38573064
Kurtosis-0.97550782
Mean18.313314
Median Absolute Deviation (MAD)4
Skewness-0.54588002
Sum54723498
Variance49.900187
MonotonicityNot monotonic
2024-05-20T21:17:16.820560image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
25 804985
26.9%
21 464230
15.5%
13 320957
 
10.7%
8 179339
 
6.0%
16 164884
 
5.5%
28 135793
 
4.5%
24 130537
 
4.4%
20 120884
 
4.0%
5 96979
 
3.2%
9 84693
 
2.8%
Other values (18) 484900
16.2%
ValueCountFrequency (%)
1 7110
 
0.2%
2 16728
 
0.6%
3 3997
 
0.1%
4 30265
 
1.0%
5 96979
3.2%
6 57254
 
1.9%
7 64062
 
2.1%
8 179339
6.0%
9 84693
2.8%
10 21995
 
0.7%
ValueCountFrequency (%)
28 135793
 
4.5%
27 18711
 
0.6%
26 18893
 
0.6%
25 804985
26.9%
24 130537
 
4.4%
23 43
 
< 0.1%
22 13101
 
0.4%
21 464230
15.5%
20 120884
 
4.0%
19 34092
 
1.1%

click_referrer_type
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8389813
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:17.611533image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1563557
Coefficient of variation (CV)0.62880232
Kurtosis9.1175335
Mean1.8389813
Median Absolute Deviation (MAD)0
Skewness2.8399665
Sum5495209
Variance1.3371585
MonotonicityNot monotonic
2024-05-20T21:17:18.331188image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 1602601
53.6%
1 1194321
40.0%
5 80766
 
2.7%
7 69798
 
2.3%
6 20455
 
0.7%
4 19820
 
0.7%
3 420
 
< 0.1%
ValueCountFrequency (%)
1 1194321
40.0%
2 1602601
53.6%
3 420
 
< 0.1%
4 19820
 
0.7%
5 80766
 
2.7%
6 20455
 
0.7%
7 69798
 
2.3%
ValueCountFrequency (%)
7 69798
 
2.3%
6 20455
 
0.7%
5 80766
 
2.7%
4 19820
 
0.7%
3 420
 
< 0.1%
2 1602601
53.6%
1 1194321
40.0%

article_id
Real number (ℝ)

HIGH CORRELATION 

Distinct46033
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194922.65
Minimum3
Maximum364046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:19.127157image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile42223
Q1124228
median202381
Q3277067
95-th percentile336254
Maximum364046
Range364043
Interquartile range (IQR)152839

Descriptive statistics

Standard deviation90768.421
Coefficient of variation (CV)0.4656638
Kurtosis-0.9430459
Mean194922.65
Median Absolute Deviation (MAD)77632
Skewness-0.12343654
Sum5.8246416 × 1011
Variance8.2389063 × 109
MonotonicityNot monotonic
2024-05-20T21:17:20.032058image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160974 37213
 
1.2%
272143 28943
 
1.0%
336221 23851
 
0.8%
234698 23499
 
0.8%
123909 23122
 
0.8%
336223 21855
 
0.7%
96210 21577
 
0.7%
162655 21062
 
0.7%
183176 20303
 
0.7%
168623 19526
 
0.7%
Other values (46023) 2747230
91.9%
ValueCountFrequency (%)
3 1
< 0.1%
27 1
< 0.1%
69 1
< 0.1%
81 2
< 0.1%
84 1
< 0.1%
94 2
< 0.1%
115 2
< 0.1%
125 1
< 0.1%
137 1
< 0.1%
139 1
< 0.1%
ValueCountFrequency (%)
364046 2
 
< 0.1%
364043 8
 
< 0.1%
364028 1
 
< 0.1%
364022 1
 
< 0.1%
364017 22
< 0.1%
364015 1
 
< 0.1%
364014 1
 
< 0.1%
364013 1
 
< 0.1%
364012 1
 
< 0.1%
364001 4
 
< 0.1%

category_id
Real number (ℝ)

HIGH CORRELATION 

Distinct316
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.93824
Minimum1
Maximum460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:20.926978image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile67
Q1250
median327
Q3409
95-th percentile437
Maximum460
Range459
Interquartile range (IQR)159

Descriptive statistics

Standard deviation113.08055
Coefficient of variation (CV)0.36961887
Kurtosis0.10954235
Mean305.93824
Median Absolute Deviation (MAD)77
Skewness-0.88776697
Sum9.1419884 × 108
Variance12787.21
MonotonicityNot monotonic
2024-05-20T21:17:21.888564image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
281 370843
 
12.4%
375 268257
 
9.0%
412 178894
 
6.0%
437 157085
 
5.3%
250 140454
 
4.7%
331 115901
 
3.9%
399 104464
 
3.5%
209 83750
 
2.8%
418 67119
 
2.2%
118 64216
 
2.1%
Other values (306) 1437198
48.1%
ValueCountFrequency (%)
1 6107
 
0.2%
2 3742
 
0.1%
3 1
 
< 0.1%
4 2856
 
0.1%
6 9971
0.3%
7 19898
0.7%
9 15470
0.5%
11 2
 
< 0.1%
15 48
 
< 0.1%
16 135
 
< 0.1%
ValueCountFrequency (%)
460 12
 
< 0.1%
458 1230
 
< 0.1%
456 11
 
< 0.1%
455 11042
0.4%
454 102
 
< 0.1%
453 5
 
< 0.1%
451 2
 
< 0.1%
450 4830
0.2%
449 3
 
< 0.1%
448 4436
0.1%

created_at_ts
Real number (ℝ)

HIGH CORRELATION 

Distinct45785
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5067506 × 1012
Minimum1.1665728 × 1012
Maximum1.510666 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:23.335649image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.1665728 × 1012
5-th percentile1.5068604 × 1012
Q11.5070534 × 1012
median1.5074034 × 1012
Q31.5077167 × 1012
95-th percentile1.5081064 × 1012
Maximum1.510666 × 1012
Range3.4409321 × 1011
Interquartile range (IQR)6.63278 × 108

Descriptive statistics

Standard deviation7.068639 × 109
Coefficient of variation (CV)0.0046913131
Kurtosis212.69382
Mean1.5067506 × 1012
Median Absolute Deviation (MAD)3.2015 × 108
Skewness-13.569876
Sum4.5024436 × 1018
Variance4.9965657 × 1019
MonotonicityNot monotonic
2024-05-20T21:17:24.380446image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.506912747 × 101237213
 
1.2%
1.50696187 × 101228943
 
1.0%
1.507613161 × 101223851
 
0.8%
1.507618597 × 101223499
 
0.8%
1.507198955 × 101223122
 
0.8%
1.5075557 × 101221855
 
0.7%
1.507798791 × 101221577
 
0.7%
1.50694961 × 101221062
 
0.7%
1.507731529 × 101220303
 
0.7%
1.50714405 × 101219526
 
0.7%
Other values (45775) 2747230
91.9%
ValueCountFrequency (%)
1.1665728 × 10121
 
< 0.1%
1.173262501 × 10121
 
< 0.1%
1.187857895 × 10121
 
< 0.1%
1.211992068 × 10121
 
< 0.1%
1.265812331 × 10124
< 0.1%
1.268843758 × 10121
 
< 0.1%
1.269450239 × 10121
 
< 0.1%
1.270070507 × 10121
 
< 0.1%
1.270838375 × 10121
 
< 0.1%
1.271189174 × 10121
 
< 0.1%
ValueCountFrequency (%)
1.510666014 × 10121
< 0.1%
1.510577019 × 10121
< 0.1%
1.510076775 × 10121
< 0.1%
1.510071471 × 10121
< 0.1%
1.509949218 × 10121
< 0.1%
1.509733244 × 10121
< 0.1%
1.509720011 × 10121
< 0.1%
1.509700988 × 10121
< 0.1%
1.509693065 × 10121
< 0.1%
1.509690207 × 10121
< 0.1%

publisher_id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 MiB
0
2988181 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2988181
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2988181
100.0%

Length

2024-05-20T21:17:25.355656image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-20T21:17:25.917901image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
0 2988181
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2988181
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2988181
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2988181
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2988181
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2988181
100.0%

words_count
Real number (ℝ)

Distinct536
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.62834
Minimum0
Maximum6690
Zeros65
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size22.8 MiB
2024-05-20T21:17:26.566434image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile136
Q1173
median198
Q3232
95-th percentile284
Maximum6690
Range6690
Interquartile range (IQR)59

Descriptive statistics

Standard deviation81.60152
Coefficient of variation (CV)0.39113344
Kurtosis79.67854
Mean208.62834
Median Absolute Deviation (MAD)28
Skewness6.5503772
Sum6.2341924 × 108
Variance6658.8081
MonotonicityNot monotonic
2024-05-20T21:17:27.457662image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184 62994
 
2.1%
158 60457
 
2.0%
197 58150
 
1.9%
210 56408
 
1.9%
259 49572
 
1.7%
183 44730
 
1.5%
199 42994
 
1.4%
205 42918
 
1.4%
198 40228
 
1.3%
220 39454
 
1.3%
Other values (526) 2490276
83.3%
ValueCountFrequency (%)
0 65
 
< 0.1%
5 1
 
< 0.1%
7 11
 
< 0.1%
8 137
 
< 0.1%
10 559
< 0.1%
11 9
 
< 0.1%
12 19
 
< 0.1%
13 3
 
< 0.1%
14 1279
< 0.1%
15 5
 
< 0.1%
ValueCountFrequency (%)
6690 1
 
< 0.1%
3808 7
< 0.1%
3082 5
< 0.1%
2899 1
 
< 0.1%
2743 4
< 0.1%
1764 8
< 0.1%
1676 2
 
< 0.1%
1635 3
 
< 0.1%
1626 2
 
< 0.1%
1606 1
 
< 0.1%

Interactions

2024-05-20T21:16:10.702859image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:28.091524image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:46.727964image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:05.040413image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:23.338704image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:41.139346image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:00.579442image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:19.936028image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:37.436629image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:55.920317image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:14.558410image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:33.837512image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:52.318896image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:12.379023image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:29.497922image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:48.130264image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:06.375700image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:24.919571image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:42.572137image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:02.047910image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:21.318771image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:38.816115image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:57.366196image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:15.977977image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:35.241333image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:53.681468image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:13.932436image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:30.945780image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:49.557449image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:07.714270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:26.299359image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:44.208474image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:03.958730image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:22.681634image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:40.314209image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:58.821999image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:17.409308image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:36.728641image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:55.072941image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:15.367935image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:32.374436image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:50.941271image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:09.438020image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:27.670153image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:45.607442image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:05.486683image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:24.080868image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:41.825538image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:00.289295image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:18.869543image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:38.198831image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:56.546957image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:16.851866image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:33.738456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:52.403084image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:10.766182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:29.004351image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:46.972488image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:06.954001image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:25.376515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:43.244190image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:02.074448image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:20.401871image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:39.623881image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:58.222533image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:18.382193image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:35.193029image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:53.813557image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:12.201193image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:30.326553image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:48.353782image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:08.525306image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:26.708792image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:44.640242image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:03.487985image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:21.898686image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:41.077260image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:59.701714image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:19.978823image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:36.811787image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:55.191703image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:13.588469image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:31.670577image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:49.810365image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:10.043784image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:28.075931image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:46.007479image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:04.856747image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:23.488385image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:42.495151image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:01.143951image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:21.356354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:38.145210image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:56.495301image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:14.912860image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:32.973304image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:51.137620image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:11.368245image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:29.366091image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:47.377046image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:06.163698image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:25.121067image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:43.870100image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:02.466095image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:22.740183image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:39.545591image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:57.939704image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:16.291783image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:34.306984image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:52.711451image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:12.761255image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:30.646183image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:48.662375image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:07.475199image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:26.616641image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:45.245702image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:03.791857image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:24.247874image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:41.029167image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:59.390476image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:17.669920image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:35.700907image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:54.289430image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:14.121129image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:31.940208image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:50.049655image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:08.898166image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:28.015549image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:46.696537image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:05.219569image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:25.689648image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:42.423184image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:00.875775image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:19.117387image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:37.072709image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:55.803300image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:15.522513image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:33.265589image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:51.545121image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:10.320136image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:29.469929image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:48.087217image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:06.607586image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:27.137905image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:43.735316image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:02.199914image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:20.455862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:38.375270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:57.362474image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:16.892050image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:34.539431image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:52.869276image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:11.648404image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:30.866930image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:49.474524image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:07.936580image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:28.615536image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:12:45.259165image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:03.671753image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:21.879712image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:39.792511image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:13:58.963166image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:18.423854image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:35.999962image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:14:54.289058image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:13.038644image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:32.386925image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:15:50.985048image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-20T21:16:09.281888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-05-20T21:17:28.172642image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
article_idcategory_idclick_countryclick_deviceGroupclick_environmentclick_osclick_referrer_typeclick_regionclick_timestampcreated_at_tssession_idsession_sizesession_startuser_idwords_count
article_id1.0000.998-0.0090.0280.063-0.0020.0470.1090.0620.0810.062-0.0210.062-0.000-0.122
category_id0.9981.000-0.0090.0330.069-0.0020.0480.1090.0660.0850.066-0.0210.0660.002-0.125
click_country-0.009-0.0091.0000.0500.0470.0800.0210.365-0.006-0.003-0.006-0.012-0.006-0.0340.014
click_deviceGroup0.0280.0330.0501.0000.325-0.3210.0530.0460.0250.0370.028-0.1600.028-0.0430.006
click_environment0.0630.0690.0470.3251.000-0.001-0.041-0.031-0.007-0.010-0.0080.033-0.0080.0220.002
click_os-0.002-0.0020.080-0.321-0.0011.000-0.0010.037-0.020-0.020-0.0210.070-0.021-0.0270.005
click_referrer_type0.0470.0480.0210.053-0.041-0.0011.0000.030-0.017-0.030-0.016-0.313-0.0160.0670.042
click_region0.1090.1090.3650.046-0.0310.0370.0301.0000.0010.0030.001-0.0170.001-0.024-0.004
click_timestamp0.0620.066-0.0060.025-0.007-0.020-0.0170.0011.0000.9450.9990.0080.9990.252-0.105
created_at_ts0.0810.085-0.0030.037-0.010-0.020-0.0300.0030.9451.0000.944-0.0020.9440.220-0.089
session_id0.0620.066-0.0060.028-0.008-0.021-0.0160.0010.9990.9441.0000.0021.0000.253-0.105
session_size-0.021-0.021-0.012-0.1600.0330.070-0.313-0.0170.008-0.0020.0021.0000.002-0.156-0.040
session_start0.0620.066-0.0060.028-0.008-0.021-0.0160.0010.9990.9441.0000.0021.0000.253-0.105
user_id-0.0000.002-0.034-0.0430.022-0.0270.067-0.0240.2520.2200.253-0.1560.2531.000-0.044
words_count-0.122-0.1250.0140.0060.0020.0050.042-0.004-0.105-0.089-0.105-0.040-0.105-0.0441.000

Missing values

2024-05-20T21:16:29.669662image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-20T21:16:38.242509image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

user_idsession_idsession_startsession_sizeclick_timestampclick_environmentclick_deviceGroupclick_osclick_countryclick_regionclick_referrer_typearticle_idcategory_idcreated_at_tspublisher_idwords_count
012590215076461811644361507646181000315076462053904117125130008242815076179110000285
112590215076461811644361507646181000315076462406784117125115733928115075675730000184
212590215076461811644361507646181000315076462706784117125131442443115076232050000236
3723715076461818344371507646181000215076463163864117121215696428115076274390000135
472371507646181834437150764618100021507646346386411712126440913415076286850000268
5555751507646182160438150764618200021507646183873411712556440913415076286850000268
65557515076461821604381507646182000215076462138734117125523587037515076213240000163
713073915076461822404391507646182000215076469464434117121223633837515076315830000182
813073915076461822404391507646182000215076469764434117121233622143715076131610000158
97766915076461837234401507646183000215076474454264117125223469837515076185970000183
user_idsession_idsession_startsession_sizeclick_timestampclick_environmentclick_deviceGroupclick_osclick_countryclick_regionclick_referrer_typearticle_idcategory_idcreated_at_tspublisher_idwords_count
29881715718315072645531474771507264553000315072667163494320124116201628115072442040000261
29881725718315072645531474771507264553000315072673724344320124129855342815072441190000120
29881735718315072645531474771507264553000315072674024344320124115850928115071848860000265
2988174695501507264564108478150726456400021507264973646432121127697040915071872550000197
2988175695501507264564108478150726456400021507265003646432121112417725015072424970000161
29881768695815072645643964791507264564000315072646964374321028125494938915071463880000147
29881778695815072645643964791507264564000315072647711734321028123580437515072037960000257
29881788695815072645643964791507264564000315072648011734321028123620737515071845020000199
29881792780615072645752764801507264575000215072650721004117125220779733115072361790000258
29881802780615072645752764801507264575000215072651021004117125216142528115072173400000181